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This study was designed to improve the explanation for the behavior of the phenomenon of technology convergence. The concepts and measurements of diversity and persistence, as inherent attributes of the phenomenon, were elaborated by reviewing different theories. Diversity was examined by analyzing the degree of capability to absorb heterogeneous t...
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... The era of convergence in the field of information and communication technology has transformed the industrial landscape and brought about changes. These changes pertain to the development of technology in order to accommodate technological advancements and innovations for future progress (Shim et al. 2016). ...
The development of information media in line with global advancements has facilitated access to communication and the exchange of information for individuals worldwide. Radio Republik Indonesia (RRI), as a public broadcasting medium, has adapted to the changing media landscape through the implementation of the RRI Play Go application. This study aims to analyze the development and implementation of RRI Play Go, focusing on RRI Meulaboh. A qualitative descriptive method was employed, involving direct observation and interviews with RRI Meulaboh employees. The findings reveal that RRI Play Go, as a digital radio platform, provides user-friendly features such as location-based broadcasts, access to educational content, live streaming, and interactive communication. Media convergence, facilitated by digitalization, has enabled RRI Meulaboh to maintain its relevance, expand its reach, and continue its mission of providing informative and educational content to the public.
... In terms of diversity, Shim et al. (2016) proposed a diversity measure based on convergence using the Rao-Stirling index. With this measure, they analyzed the diversity of technology using IPC classification codes. ...
Considerably little effort has been devoted to systematically exploring the landscape of government-funded innovation schemes, leaving policymakers and academics little empirical evidence with which to grasp the overall situation of national R&D funding strategies. In the United States (US), patents with a government right or financial interest are flagged, offering a window through which we can examine the landscape of today's patterns of government support for innovation. We conduct the examination from the perspectives of the leading government agencies, the promotor-recipient relationship, and the common concerns of different participants. The results show that the R&D project funding by federal agencies has, among other factors, contributed to the growth in the number of patent records. The Departments of Defense (DoD), Energy (DoE), and Health and Human Services (HHS), and the National Science Foundation (NSF) have issued the most funding and hold rights to more patent records than any other agencies. Moreover, reforms to the US patent system made 40 years ago to afford more protection to non-government assignees appear to have significantly impacted patenting activity. Universities, companies, and individuals have become far more active in fulfilling government-funded projects, with remarkable innovations as a result. In recent years, funding priorities have shifted toward research in biomedicine, fields related to human life, and computer science. However, the four dominant agencies responsible for most government funding differ in their investment priorities and frequently adjust which areas of innovation they support. This study is among the first attempts to support the landscape of the public-invested innovation using the full government-subsidized patent dataset. The analyses in this paper are instructive in understanding the dynamics of US government funding for innovation and informing effective policymaking around innovation.
... Some of them propose explanations for convergence processes from evolutionary models. These models of co-evolution of dynamics, patterns, and sectoral trajectories of industries and technologies have also been used by studies that seek to generate explanations about technological convergence from a macro perspective (emphasizing the trends of complete techno-economic sectors) and from a meso perspective (accentuating the relevance of business behaviors and strategies generated by firms in response to increasingly global sectoral trends). 2 From a macro perspective, Shim et al. (2016) point out that the behavior of convergence phenomena can be understood from the factors of diversity (the degree of a sector's capabilities to absorb heterogeneous technologies) and persistence (continuity in the use of accumulated technologies) in a technological sector. For Geum, Kim, and Lee (2016), industrial convergence is a process that is influenced by multiple factors: technology, politics, integration of social businesses, and value generation. ...
... Considering the resonance that the convergence concept has had in the framework of ITS studies and in the design of public policies in the sector, this work has sought to highlight the importance of the way the field of knowledge is structured around this concept. (2007) (2008); Karvonen and Kässi (2013) Trends in convergence in entire techno-economic sectors Broring (2013); Karvonen and Kässi (2013); Jeong and Lee (2015); Golembiewski, Sick, and Bröring (2015); Dernis, Squicciarini, and de Pinho (2016); Gauch and Blind (2015); Shim et al. (2016); Geum, Kim, and Lee (2016); Song, Elvers, and Leker (2017) (Continued ) 10 F. Stezano ...
This article explores the existence of two main perspectives on the concept of convergence. The first view assumes convergence as an epistemological, methodological and heuristic issue resulting from the confluence of scientific disciplines and technological fields. The second view emphasizes the importance of technology management and industrial application development as strategies for analyzing the technical challenges and risks associated with convergence processes in the firm. To differentiate between the two visions, 59 specialized bibliographic works selected from a theoretical sample are analyzed. The main finding of this review is the characterization of these two perspectives that, although contradictory, are part of a common conceptualization of convergence as an umbrella notion. These findings provide relevant insights for a field of knowledge under construction: policy agendas focused on fostering technological convergence should start from the differentiation of these two analytical and conceptual levels.
... The number of data utilized by Korea, which has the characteristics of the centralized database, was as high as that used by the US. It may cause a "home advantage" bias [26,27]. Thus, the data of Korea excluded the making of a co-occurrence matrix. ...
The coronavirus crisis may lead to a deeper understanding of international collaborations for developing antivirals and vaccines that are essential to protect us from current and future health security threats. Beyond technical solutions, the government of South Korea needs to establish a timely strategic investment in coronavirus-related research and development (R&D) in order to enhance the capabilities for managing this new uncertainty in regard to the domestic health crisis. Thus, this study aims to provide useful information about the status of global coronavirus-related research from the South Korean government’s perspective. National funded projects stemmed from leading nations such as the United States, countries of the European Union, and Japan between 2012 and 2018. Six research fields were derived by clustering analysis and an expert-based approach, and then matched to those of South Korea. The comparative analysis among them allowed for the identification of the nations’ strengths and weaknesses, thereby laying the groundwork for strategic international research collaborations.
... Convergence can be found in patent data through growing overlap among Standard Industrial Classification (SIC) codes or International Patent Classification (IPC) codes and through an increase in patent citations among different classes (Pennings & Puranam, 2001). Many researchers make use of the IPC codes to illustrate the patterns of converging technologies (Dosi, 1982;Matti & Tuomo, 2011;Shim et al., 2016;Verbeek et al., 2002). IPC hierarchically structures patents into section (1-digit), classes (3-digit), subclasses (4-digit), main groups, and subgroups. ...
Technological Convergence (TC) reflects developmental processes that overlap different technological fields. It holds promise to yield outcomes that exceed the sum of its subparts. Measuring emergence for a TC environment can inform innovation management. This paper suggests a novel approach to identify Emergent Topics (ETopics) of the TC environment within a target technology domain using patent information. A non-TC environment is constructed as a comparison group. First, TC is operationalized as a co-classification of a given patent into multiple 4-digit IPC codes (≥2-IPC). We take a set of patents and parse those into three sub-datasets based on the number of IPC codes assigned 1-IPC (Non-TC), 2-IPC and ≥3-IPC. Second, a method is applied to identify emergent terms (ETs) and calculate emergence score for each term in each sub-dataset. Finally, we cluster those ETs using Principal Components Analysis (PCA) to generate a factor map with ETopics. A convergent domain – 3D printing – is selected to present the illustrative results. Results affirm that for 3D printing, emergent topics in TC patents are distinctly different from those in non-TC patents. The number of ETs in the TC environment is increasing annually.
... These perspectives were found in the work of Brusoni and Geuna [31] and of Shim, Kwon, Moon, and Kim [32]. Brusoni and Geuna [31] proposed the theoretical framework of knowledge specialization with the concept of knowledge persistence, meaning the cumulative and path dependent process of knowledge production and accumulation and that of knowledge integration, implying the process of combining different types of innovative activities. ...
... Brusoni and Geuna [31] proposed the theoretical framework of knowledge specialization with the concept of knowledge persistence, meaning the cumulative and path dependent process of knowledge production and accumulation and that of knowledge integration, implying the process of combining different types of innovative activities. In lieu of investigating the convergent patterns of nations' sectoral knowledge bases in the previous study, Shim Kwon, Moon, and Kim [32] concentrated on the patterns of technological knowledge progression (or evolution) with the concept of persistence, defined as the degree of continuity in the usage of cumulated knowledge set and diversity, defined as the degree of capability to absorb different knowledge (e.g., technology). ...
... On the basis of such viewpoint, the evolution of knowledge can be defined as a process of combining aggregated useful knowledge that formed by self-sustained continuously usage for the improvement of current areas with heterogeneous useful knowledge that adopted to make new products or services. In the previous study [32], the conceptual approach to the phenomenon of technology convergence was explained with combining both persistence and diversity, and it has the potential to apply to any social study that is based on the idea that the source of organizational competence is derived from the integration of specialized knowledge [39]. The aim of this study is identical to that of investigating the integration competences on technology convergence, which is a course of integrating knowledge [40]. ...
—This article made a fresh attempt to deduce a consensus on definition of knowledge per se and valid measurements for it, thereby providing better understanding the advanced knowledge-based economy. By reviewing literatures, we identified the conceptual approach to the phenomenon of technology convergence was identical to that of knowledge evolution. With two – persistence and diversity – dimensions, the dynamic patterns of knowledge utilization of OECD and G20 nations are explained during 1991-2015. The results indicate the existence of four knowledge groups characterized by markedly different degrees of development from the technology perspective. Most highly industrialized nations such as Untied States, Germany, and Korea have maintained their knowledge utilization capabilities in high levels. On the contrary, developing countries such as Indonesia, Mexico, and Czech Republic have struggled to develop the depth of knowledge. The value of suggested indicators for knowledge utilization capabilities for
guiding public policy and cooperative strategy finally discussed.
... These perspectives were found in the work of Brusoni and Geuna [31] and of Shim, Kwon, Moon, and Kim [32]. Brusoni and Geuna [31] proposed the theoretical framework of knowledge specialization with the concept of knowledge persistence, meaning the cumulative and path dependent process of knowledge production and accumulation and that of knowledge integration, implying the process of combining different types of innovative activities. ...
... Brusoni and Geuna [31] proposed the theoretical framework of knowledge specialization with the concept of knowledge persistence, meaning the cumulative and path dependent process of knowledge production and accumulation and that of knowledge integration, implying the process of combining different types of innovative activities. In lieu of investigating the convergent patterns of nations' sectoral knowledge bases in the previous study, Shim Kwon, Moon, and Kim [32] concentrated on the patterns of technological knowledge progression (or evolution) with the concept of persistence, defined as the degree of continuity in the usage of cumulated knowledge set and diversity, defined as the degree of capability to absorb different knowledge (e.g., technology). ...
... On the basis of such viewpoint, the evolution of knowledge can be defined as a process of combining aggregated useful knowledge that formed by self-sustained continuously usage for the improvement of current areas with heterogeneous useful knowledge that adopted to make new products or services. In the previous study [32], the conceptual approach to the phenomenon of technology convergence was explained with combining both persistence and diversity, and it has the potential to apply to any social study that is based on the idea that the source of organizational competence is derived from the integration of specialized knowledge [39]. The aim of this study is identical to that of investigating the integration competences on technology convergence, which is a course of integrating knowledge [40]. ...
As a driving force behind innovation, technological fusion has emerged as a prevailing trend in knowledge innovation. However, current research lacks the semantic analysis and identification of knowledge fusion across technological domains. To bridge this gap, we propose a strategy that combines the latent Dirichlet allocation (LDA) topic model and the Doc2vec neural network semantic model to identify fusion topics across various technology domains. Then, we fuse the semantic information of patents to measure the characteristics of fusion topics in terms of knowledge diversity, homogeneity and cohesion. Applying this method to a case study in the fields of digital medicine and machine learning, we identify six fusion topics from two technology domains, revealing two distinct trends: diffusion from the center to the periphery and clustering from the periphery to the center. The study shows that the fusion measure of topic-semantic granularity can reveal the variability of technology fusion processes at a profound level. The proposed research method will benefit scholars in conducting multi-domain technology fusion research and gaining a deeper understanding of the knowledge fusion process across technology domains from a semantic perspective.
> The aim of this study is to provide the dynamic convergence index that reflected the inherent characteristics of the convergence phenomenon and utilized the nationally-funded R&D projects data, thereby suggesting useful information about the direction of the national convergence R&D strategy. The dynamic convergence index that we suggested was made of two indicators: persistency and diversity. From a time-series perspective, the persistency index, which measures the degree of continuous convergence of multidisciplinary nationally-funded R&D projects, and the diversity index, which measures the degree of binding with heterogeneous research areas. We conducted the empirical experiment with 151,248 convergence R&D projects during the 2015∼2021 time period. The results showed that convergence R&D projects in both public health and life sciences appeared the highest degree of persistency. It was presumed that the degree of persistency has increased again due to the COVID-19 pandemic. Meanwhile, the degree of diversity has risen with combining with disciplinary such as materials, chemical engineering, and brain science areas to solve social problems including mental health, depression, and aging. This study not only provides implications for improving the concept and definition of dynamic convergence in terms of persistency and diversity for national convergence R&D strategy but also presented dynamic convergence index and analysis methods that can be practically applied for directing public R&D programs.
